Research Scientist, Safety Oversight, DeepMind

Google isn't just a software company. The Hardware Operations team is responsible for monitoring the state-of-the-art physical infrastructure behind Google's powerful search technology. As an Operations Technician, you'll install, configure, test, troubleshoot and maintain hardware (like servers and its components) and server software (like Google's Linux cluster). You'll also take on the configuration of more complex components such as networks, routers, hubs, bridges, switches and networking protocols. You'll participate in or lead small project teams on larger installations and develop project contingency plans. A typical day involves manual movement and installation of racks, and while it can sometimes be physically demanding, you are excited to work with infrastructure that is at the cutting-edge of computer technology. The AI and Infrastructure team is redefining what’s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide. We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.

Responsibilities

• Build classifiers and data pipelines to detect model misbehavior and misuse end-to-end.

• Research and develop cross-context monitoring systems to detect coordinated harms, developing novel signal aggregation methods across disparate user sessions to identify large-scale attack vectors.

• Think critically about novel methods for monitoring using model activations, actions, chains-of-thought and final answers.

• Collaborate closely with infrastructure teams and data scientists to scale your work and regularly share results with the wider safety team.

Qualifications Minimum qualifications:

• PhD in Computer Science, a related field, or equivalent practical experience.

• Experience in the domain area of generative AI and Large Language Models (LLM).

• Experience building and shipping technical products.

Preferred qualifications:

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.

• 3 years of experience developing code, running experiments and analyses collaboratively with coding agents.

• Experience building highly parallelised data pipelines, working on data quality, automated evaluation design and simple statistical modeling.

• Proven ability in approaching new research questions and implementing technical solutions for them at scale.

• Ability to use AI every day to build and find ways to push the frontier of model capabilities to accelerate work.